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AWS Manufacturing.pdf

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AWS Manufacturing.pdf

  1. 1. AWS in Manufacturing What role can AWS have in your transformation? Michel Putnik WW BD Lead, Manufacturing mputnik@amazon.com
  2. 2. The true value of digital © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.2 Revenue Growth Operational Overhead Empowered Sales Teams Increased Efficiency Intelligent Decision Making Products that Get Better with Time Better Relationship with Customers Data Driven Discipline
  3. 3. The 4th Industrial Revolution © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.3 Industry 1.0 Mechanical production powered by water and steam Industry 2.0 Mass production based on the division of labor and powered by electrical energy Industry 3.0 Electronics and IT for a further automation of production Industrie 4.0 Cyber physical production systems 18th Century 20th Century 1970s Today
  4. 4. Industry 4.0 4 Autonomous Robots Simulation & HPC Vertical & Horizontal Integration Industrial Internet of Things Cybersecurity Cloud Additive Manufacturing Augmented Reality Big Data ML, Analytics Technical enablersCommon use cases • Smart Factory • Smart Products & Services • ML driven Quality Control • ML based forecasting • ML based planning • Self driving logistics vehicles • Digital Twin • Smart Supply chains • Predictive Maintenance • Self organizing production • Disaster recovery • SAP on AWS • Knowledge Transfer of maintenance/service staff
  5. 5. What sets AWS apart? © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.5 Security Fine-grained control Service Breadth & Depth Pace of Innovation 120+ services to support any cloud workload; rapid customer driven releases Experience: 1M+ customers Building and managing cloud since 2006 Global Footprint 18 regions, 55 availability zones, 121 edge locations Artificial Intelligence Fully integrated in AWS Ecosystem Thousands of partners; 3,800+ Marketplace products Enterprise Leader AWS is positioned highest in execution and furthest in vision within the Leaders Quadrant
  6. 6. Two predominant outcomes © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.6 Smart products and services are brought to market with smart factories Smart Factories Smart Products and Services Connectivity and Internet Technology Smart Sensors and Actuators Cloud Processing and Storage Big Data Analytics and Artificial Intelligence
  7. 7. Smart factories built on cloud computing © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.7 Smart factories – simple and adaptive Global Data and Integration Platform Internal Focus applications Processes Employees Equipment • Highly reliable • Highly available • Increased agility • Increased innovation • Lower total cost • Knowledge capture
  8. 8. applications Smart products built on cloud computing © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.8 Smart products and services – individualized and quickly brought to market Global Data and Integration Platform Processes Employees Equipment • Rich and adaptive customer experience • Innovation and quickly bring to market • Smart, connected and updated External Focus applications
  9. 9. Manufacturing Operations Business Matrix Plant Manager Quality Manager H&S Officer Production Planner Plant Maintenance Performance Quality Availability Safety Product Increase/Optimize Production line throughput Optimize Production Line throughput Optimize Asset Lifecycle Reduce Scrap/Defects Reduce Scrap/Defects Reduce unplanned outages / stoppages No unplanned outages Zero safety incidents Increase Quality Build to Order Optimize Supply Chain Build to Order Minimize Stock Production Manager Protect workforce Safe Environment Asset Maintenance Track Inventory Reduce Rework Build to Plan Engineer Reduce Engineering Change Orders Reduce Design Time Enable safe work environment Representative
  10. 10. Envisioning Example Business Outcomes / Goals Enabling Technologies Stakeholders Increase Performance Increase Quality Plant Manager Production Planner Quality Manager Plant Manager Metrics Increase Availability Line Utilization M O Stoppage Time M O % of rework M O M O Optimized Production Throughput Implement JiT Inventory No unplanned downtime Reduce rework Production Planning Forecasting ML Data Lake Deep Learning Video Defect Detection Analytics for Predictive Maintenance
  11. 11. ISA-95 triangle in the context of the AWS Cloud Level 1 Level 2 Line/Machine Control Animation Direct Control Level 3 Level 4 Description Line/Machine Supervision Manufacturing Operations Management Business Planning & Logistics MES/ Historian ERP/PLP/SCM App/SystemFunction Line/Cell Execution Business Operations SCADA/HMI Supervisory Control DCS/PLC/RTU Level 0 Physical Values Raw Data Event Signals I/O Sensor AWS Architecture Enterprise Apps in the Cloud Data Ingestion & Analytics Edge / Greengrass IoT Device
  12. 12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. AWS Manufacturing Reference Architecture (Brownfield) Greengrass S3 Data Lake Kinesis Firehose MES Factory Machines Protocol conversion ML Inference AWS IoT Sage Maker Machine Learning Amazon QuickSight Data Visualization / Reporting Amazon Athena Historian Storage Gateway EMR Amazon EBC Amazon EC2 AWS Batch Amazon AppStream Amazon EBC Amazon EC2 HPC Workloads Enterprise Workloads (SAP) DMS RDS Local Servers RedShift Data Warehouse DataIngestion API Gateway Interfaces N:1 Plant Manager Quality Manager H&S Officer Production Planner Plant Maintenance Production Manager Engineer OSI PI Connector Snowball Edge Data Migration
  13. 13. Thank you! © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.13

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